TL;DR

Machine Learning Engineer - Pricing (AI): Building and maintaining ML models to deliver highly impactful pricing recommendations and optimized interactions across PlayStation experiences with an accent on quantifying product price-elasticity, refining time-series forecasting, and developing optimization workflows. Focus on architecting and building delightful production-grade ML systems and applying state-of-the-art machine learning and deep learning technologies.

Location: Must be based in the USA

Company

%hirify_global% is a global leader in entertainment, producing PlayStation products and services, and striving to create an inclusive and diverse environment for its global team.

What you will do

Build and maintain ML models that quantify product price-elasticity and cannibalization effects.
Refine time-series forecasting algorithms to predict demand across multiple regions and product lines.
Develop optimization workflows using OR-Tools to balance sales growth and business constraints.
Refine clustering algorithms to identify lookalike products for smarter pricing and promotional strategies.
Apply a broad spectrum of state-of-the-art machine learning and deep learning technologies.
Build scalable and resilient ML systems along with appropriate monitoring and continuous evaluation frameworks.
Work closely with cross-functional partners to translate requirements into effective, scalable, ML-driven solutions.

Requirements

Advanced degree (Master’s or Ph.D.) in CS/Statistics/Data Science/Operations Research/Econometrics, specializing in machine learning and optimization.
1+ years of industry experience applying time-series models in production, with hands-on experience in forecasting libraries (e.g., LightGBM, Prophet).
Proven track record with mixed-integer programming or constraint solvers for pricing or resource allocation.
Strong programming skills in Python, Java, with proficiency in ML libraries and frameworks (TensorFlow, PyTorch, Spark Mlib, scikit-learn).
Good ML systems engineering experience (job orchestration, training pipelines, deployment, serving, monitoring).
Expertise in measuring the performance of unsupervised and supervised models.
Experience with software engineering principles, modern ML tech stacks, and use of Databricks, Tecton, Snowflake, and cloud services like AWS.

Nice to have

Previously worked with revenue-management systems.
Experience in a variety of machine learning and AI techniques.
Experience working in fast-paced environments on business-critical missions.
Good communication skills and the ability to convey complex ML concepts to a non-ML audience.
Experience in e-commerce, digital goods, or gaming industries.
Experience with recommender systems and similarity matching algorithms.
Background in experimentation design, causal inference, uplift modeling, and online A/B testing frameworks.

Culture & Benefits

Join a global leader in entertainment with a passion for innovation, technology, and play.
Work within an inclusive environment that empowers employees and embraces diversity.
Contribute to a growing global team focused on enhancing the PlayStation experience for millions of users.
Work on a project backed by executive leadership poised to significantly influence revenue and user engagement.
Sony is an Equal Opportunity Employer and a Fair Chance employer.

Hiring process

%hirify_global% conducts background checks at the offer stage for all new employees.